Jéssyka Vilela

Com o avanço da Inteligência Artificial (IA) em diversos setores, cresce a necessidade de compreender como os profissionais da área lidam com questões éticas no desenvolvimento dessas tecnologias. Este estudo tem como objetivo investigar as percepções de profissionais brasileiros de IA sobre ética, bem como os principais desafios enfrentados na tentativa de aplicar princípios éticos em suas práticas cotidianas. Para isso, foi conduzido um estudo de replicação com a aplicação de um survey com 39 profissionais de IA, com período de coleta de respostas entre 28 de maio e 1º de julho de 2025. Entre as diferenças identificadas comparando o trabalho original e este, destaca-se que, enquanto no estudo internacional a principal fonte de conhecimento sobre ética em IA era o ambiente organizacional, no Brasil o aprendizado foi predominantemente acadêmico. Também foi mais evidente, no contexto brasileiro, a ausência de suporte institucional e o desalinhamento entre cultura organizacional e valores éticos. Portanto, os achados deste estudo podem apoiar iniciativas futuras voltadas ao fortalecimento da ética em IA no contexto brasileiro.

Context: Computing education must go beyond technical training to encompass the development of professional competencies. Objective: This paper aims to characterize the evolution of students’ perceptions regarding the importance and difficulty of four professional competencies throughout a semester-long integrated project involving three disciplines: Business Process Management (BPM), project management, and enterprise management systems. Method: Forty-seven undergraduate students worked in multidisciplinary teams to solve real-world problems using Business Process Management Notation (BPMN) and interface prototyping. At the end of each of the four project cycles, students assessed the perceived importance and difficulty of teamwork, project planning, client negotiation, and technical challenges. The results showed that while students consistently rated all competencies as highly important, they perceived increasing difficulty over time, particularly in teamwork and project planning. This trend indicates a growing awareness of the complexity of non-technical skills. Conclusions: The use of cyclical self-assessment effectively revealed behavioral patterns and learning needs, offering valuable insights into human behavior in software education and supporting more integrated curriculum strategies.

A interseção entre saúde e tecnologia tem recebido bastante atenção nos últimos anos diante do surgimento de aplicativos de saúde. Um subgrupo desse ecossistema é o de aplicativos focados em saúde reprodutiva feminina, os quais são limitados quando o quesito é proteger a privacidade dos dados de suas usuárias. Nesse contexto, este estudo visou investigar a percepção de usuárias sobre a privacidade dos dados coletados por esses apps. Um questionário foi elaborado e respondido por 595 mulheres. Os resultados mostram que mulheres já percebem a falta de controle que tem sobre os seus dados nesses aplicativos, e algumas já os deixaram de usar por esse motivo. A partir deste estudo, várias melhorias nos aplicativos foram recomendadas.

Contexto: a modelagem de ameaças é uma atividade importante para a segurança, mas o seu uso no desenvolvimento ágil é difícil. Problema: para que a modelagem de ameaças seja aplicada no desenvolvimento ágil, é necessário entender seus desafios e boas práticas. Método: para compreender qual o cenário atual do uso de threat modeling em metodologias ágeis, foi feita uma RSL utilizando bibliotecas digitais e snowballing para obter artigos que pudessem responder às perguntas de pesquisa. Resultados: o estudo identificou os desafios, práticas e ferramentas utilizadas. Contribuições: o estudo trouxe as principais tendências da área estudada.

Context: Business Process Management (BPM) has proven to be an essential practice for optimizing operational efficiency, especially in public institutions that face complex challenges related to hierarchical rigidity and the implementation of organizational changes. Problem: The lack of BPM maturity models tailored to the public sector creates significant gaps in the ability of government organizations to assess and improve their BPM competencies. Without a clear framework, these institutions struggle to improve their processes and reach higher levels of maturity. Solution: This work proposes a BPM maturity model specifically developed for public institutions, aiming to support the gradual evolution of their process management competencies. The model includes six key factors and 51 capability areas, along with five maturity levels that provide clear guidelines for implementation. IS Theory: The research is based on the Design Science Research (DSR) approach, which guides the development and evaluation of practical artifacts and theoretical contributions. The proposed model aims to contribute to the BPM maturity theory, especially in the public context. Method: The study was conducted through a case study in a Brazilian public institution, where the maturity model was applied to assess the current BPM level. The evaluation was supported by a spreadsheet tool that automates the maturity level verification process. Results: The maturity model evaluation revealed that the public institution studied had not yet reached maturity level two, indicating the need for significant improvements in strategic areas. The assessments highlighted the model’s usefulness as a practical tool for identifying deficiencies and outlining clear action plans. Contributions and Impact: This work contributes to the field of Information Systems (IS) by offering a maturity model adapted to the public sector, providing a practical and prescriptive approach to improving business process management.

Context: The adoption of Big Data Analytics (BDA) in organizational process management has been consolidated as a transformative strategy for organizations. The use of tools and methods based on advanced digital technologies supports decision-making more efficiently. Such practices generate benefits by optimizing managerial processes, increasing productivity, and enhancing strategic decisions. Problem: However, BDA implementation faces challenges such as the integration of large data volumes, privacy, ethics, and the lack of advanced analytical skills. In this sense, companies must invest both in technological infrastructure and in cultural changes. Objective: This paper analyzes how BDA have been applied in organizational process management and how they guide decision-making in the business context. Method: We conducted a systematic literature review, analyzing 176 empirical and theoretical studies published between 2019 and 2024 across five major databases. Results: The findings reveal a set of widely adopted methods and tools, including machine learning, BI/ERP systems, IoT, dashboards, and data mining frameworks, while also identifying recurrent barriers such as system integration issues, lack of analytical skills, and resistance to data-driven practices. The review highlights consistent impacts on organizational culture, including increased transparency, agility, and emphasis on evidence-based decision-making. Conclusions: The study contributes to the field by consolidating current knowledge on BDA in organizational processes, exposing research gaps, and offering insights to guide future implementations and investigations. By mapping practices, challenges, and impacts, this work supports researchers and practitioners in effectively integrating BDA to foster innovation, operational efficiency, and a robust data-driven culture.